{"type":"ScholarlyArticle","title":"Social Media-based User Embedding: A Literature Review","authors":[{"name":"Shimei Pan","slug":"shimei-pan","given":"Shimei","family":"Pan","affiliation":"Department of Information Systems , University of Maryland , Baltimore County"},{"name":"Tao Ding","slug":"tao-ding","given":"Tao","family":"Ding","affiliation":"Department of Information Systems , University of Maryland , Baltimore County"}],"abstract":"Automated representation  learning is  behind many recent success stories in machine learning. It is often used to transfer knowledge learned from a large dataset (e.g., raw text) to tasks for which only a small number of training examples are available.  In this paper, we review recent advance in learning to represent social media users in low-dimensional embeddings.   The  technology  is  critical  for creating high performance social media-based human traits and behavior models since the ground truth for assessing latent human traits and behavior is often expensive to acquire at a large scale.  In this survey, we review typical methods for learning a unified user embeddings from heterogeneous user data  (e.g., combines social media texts with images to learn a unified user representation).  Finally we point out some current issues and future directions.","doi":"10.24963/ijcai.2019/881","url":"https://ijcai.org/proceedings/2019/881","pdf":"https://ijcai.org/proceedings/2019/0881.pdf","markdown":"https://ijcai.org/proceedings/2019/881.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/881","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Survey track","track":"Survey track","number":881,"pages":{"first":6318,"last":6324},"keywords":["Machine Learning Applications: Applications of Unsupervised Learning","Humans and AI: Personalization and User Modeling","Natural Language Processing: Embeddings","Multidisciplinary Topics and Applications: Social Sciences"],"videos":[],"references":[{"position":1,"raw":"[Abel et al., 2013] F. 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